Characterization of the Hoof Bacterial Communities of Active Digital Dermatitis Lesions in Feedlot Cattle
Bibliographic record
Abstract
Digital dermatitis (DD) is a costly hoof infection, causing lameness and pain in feedlot cattle. DD lesions can develop nonlinearly through a series of clinical stages, which can be classified by Dopfer’s M-stage scoring system. This widely adopted lesion scoring system recognizes five DD stages, where M1 (early lesion), M2 (acute ulcerative lesion), and M4.1 (chronic proliferative lesion with new developing lesion) are considered active but separate stages of the disease. This study assessed the skin surface microbiota of the active DD lesions of feedlot cattle. The DD lesions from three commercial feedlots were swabbed and then scored according to Dopfer’s M-stage scoring system. Swab samples were collected from 12 M2- and 15 M4.1-stage lesions. A total of 21 control swab samples from healthy contralateral feet (DD control) were classified as stage M0. An additional six skin swabs (M0) were collected from completely healthy (CH control) cattle with no lesions. The bacterial communities of active DD lesions (M2 and M4.1) and healthy skin (M0) were profiled using 16S amplicon sequencing. Diversity analyses showed that the hoof bacterial communities of M2 and M4.1 lesions were each distinct from those of M0 skin. However, the bacterial communities between the two active lesion stages were not different from each other. A significant increase in the relative abundance of Spirochaetota and Fusobacteriota and an overall decrease in bacterial diversity contributed to the altered bacterial communities in M2 and M4.1 lesions compared to those of healthy skin (M0). Although stages M2 and M4.1 are considered clinically different stages, the lesion-associated bacterial community is similar between the two active stages.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".